The ideal candidate will contribute to the design and development of scalable AI solutions, work closely with senior architects, and collaborate with cross-functional teams.
Key Responsibilities
1. Generative AI Design & Development
a. Contribute to the design and implementation of GenAI-powered applications.
b. Translate functional requirements into efficient Python services.
c. Work with LLM orchestration frameworks (LangChain 1.0, LangGraph, OpenAI tools, custom agents).
d. Participate in PoCs and exploratory work for new GenAI capabilities.
2. Python & Cloud
a. Build and enhance RAG pipelines using embeddings, vector databases, and chunking strategies.
b. Implement basic Agentic workflows under guidance from senior team members.
c. Work with vector search systems (PGVector, FAISS, etc.).
d. Implement indexing, metadata tagging, and retrieval optimizations.
e. Exposure to MCP / tool-integration frameworks is an added advantage.
3. Collaboration
a. Participate in code reviews, design discussions, and documentation.
b. Follow best practices in coding standards, testing and DevOps
c. Collaborate with team.
Required Skills

Keyskills: ai kubernetes api development api gateway logistics react bitbucket microservices docker analytics automation data science iam devops xml programming s3 rest python github llm machine learning ai engineer gitlab flask aws